A contribution to (neuromorphic) blind deconvolution by flexible approximated Bayesian estimation

Simone Fiori
2001 Signal Processing  
Bussgang' deconvolution techniques for blind digital channels equalization rely on a Bayesian estimator of the source sequence de ned on the basis of channel/equalizer cascade model which involves the de nition of deconvolution noise. In this paper we consider four 'Bussgang' blind deconvolution algorithms for uniformly-distributed source signals and investigate their numerical performances as well as some their analytical features. Particularly, we show that the algorithm, introduced by the
more » ... sent author, provided by a exible (neuromorphic) estimator is e ective as it does not require to make any hypothesis about convolutional noise level and exhibits satisfactory numerical performances.
doi:10.1016/s0165-1684(01)00108-6 fatcat:2dsed4jmujhgnpgtdmqgawfbs4